Data Structures in Programming - Essay Example

Running head: DATA STRUCTURES IN PROGRAMMING Data Structures in Programming Affiliation April 2009 This paper presents a detailed analysis of some programming concepts. It will discuss the complex data structures and the ways in which they are used. The arrays are also main data structures of any programming language; this paper will discuss the complex design and application of arrays. The main reason behind this discussion is to access the main advantages of arrays regarding the simplification of the program development. The modular design in application programming is very effective for the better programming of the system; while this paper will also analyze this idea through the hypothetical real-world examples. The writing, designing, plus debugging computer application is a time consuming job. Of the dissimilar attributes of making computer programs of reasonable to massive complicatedness, application data structures frequently make use of a disproportionally huge portion of a computer programmers development time. A computer data structure compiler is a gathering of techniques and tools that diminishes the load of structures programming data. There consist of a numerous efforts to make a comparable compilers and now we have more better and easy working compliers those make use of these data structures to successfully supervise and handle the data. In general, data structures have good data handling by compliers have attained an extensive level of acceptance. Here we have better working of these data structures through the following performance parameter, like performance, inadequateness, avoidable difficulty, less host language limitations, as well as boundless programming scope (Chu, 1998). Here I will discuss mainly the data structures and their performance. The main data structures that are included in this discussion are complex data structures and arrays. Here it will be analyzed how these data structures provide better for the effective programming and application development. Complex data structure A complex data structure is an arrangement that holds two arrays, one obtain the actual fraction of the program complex data as well as another grip the made-up piece. These computer arrays have to be the similar dimension as well as form, even though they can have some amount of magnitude. If our computer data structure is composite, we can be liable to indicate our program data like a deposit of linked/nested IDL variables structure. As interlinked and nesting data structure variables can assist us in generating a program data structure which follows the arrangement of our program file, intensely interlinked/nested data structures can create our application program code extra hard to generate plus retain. Take an example of program that store data in numerous arrays of our defined structures in it place to a single extremely interlinked/nested data structure (Shortridge et al, 2004). If our program data structure is composite, we can be leaning to indicate our program data like a set of interlinked/nested IDL arranged program variables. Despite the fact that deeply interlinked nesting data structure variables are able to aid us to generate a data structure is able to follow the arrangement of our program, intensely nested data structures be able to create our program code extra rigid to generate in addition to maintain (Shortridge et al, 2004). Here below I have presented an example of complex data structure; rel = structNew(); rel.dad = "Tim"; rel.mom = "Liza"; rel.sist = arrayNew(1); arrayAppend(rel.sist, "Alex"); rel.brot = arrayNew(1); arrayAppend(rel.broth, "John"); arrayAppend(rel.brot, "Kelly"); If we will be able to generate a high-quality cause to generate interlinked nested data structures then we as well have need of expending those data structures dynamically, but complex data structures allows us to have a enhanced technique to handle the computer program with less involvement and less code density. We also make use of the complex data structures for plummeting the process of replicating the data structures can reason program performance troubles mainly in huge data bases (Shortridge et al, 2004). Arrays This section discusses the design and application of arrays. In this section I will evaluate how arrays help to make simpler the program development and make it less complex. In daily life we normally group related objects into units. We purchase peas by the can and eggs by the carton. In computer languages we also have to to collect jointly data items of the identical type. The most fundamental technique that achieves this is array (Lafore, 1999). Array is a data structure that facilitates in the storage of data in defined classification. We can access the data by searching all the way through its array index. This method is potential if the data file is small to be stored in the obtainable system existing memory. This is as well an advantageous process if there are a massive amount of transforms to be established to the program file. The comparatively elevated pace of interior memory be able to frequently create similar transforms more professionally than employing a scratch file (Array, 2009). An array comprises an array index (address, memory location) where the definite value stores. While in the array the starting address is zero. The size of array is predefined but cab also identifies dynamic array (Array, 2009). We make use of arrays where we have less data and more chances of frequent changes in the data. Here we avoid developing an array of huge set of data because its supervision, organization and updating is intricate job. A predefined array that is defined with a big number and not holding an adequate amount of data; this will be memory loss. Here we can store, retrieve and arrange the data items in a definite order in the array. For instance we are able to place or arrange troops for battle. Modular design In this section I will talk about the modular design. The main aim of this section is to access the benefits of modular design. In the modular design we have better capability for designing a computer program. For instance, if we divide the problem into small pieces then it becomes easier to build up the program in a less complex way (Chu, 1998). By dividing the big problem into small sub-problems we will be able to identify a relationship among the sub-problems that allows communication and understanding the transaction of data among the sub-problems. Handling such communication in the big problem is a really complicated and difficult task (Chu, 1998). In this way we can build a well defined solution for the every sub problem that allows us to handle the each component of program in an enhanced way. The error handling in modular design is very easy. An error in a sub-problem can be identified and determined in a better way. The modular design allows designing a system that can be easily changed when we need. Such as if we want to add new functionalities in the system then we will only update that part of system, in this way we can save lot of effort and overhead of overall system change (Lafore, 1999). Conclusion This research has outlined few data structures concepts and system modular design approach. This paper has identified the main benefits of the complex data structures and their potential implementations. Also we have discussed arrays, where it is identified that how the arrays are beneficial and used in certain conditions. The last section has outlined the modular design, where I have identified the potential advantages of the modular design. References 1. [Array, 2009], Source: http://sketch.cs.berkeley.edu/wiki/index.php/Development/Code_overview, retrieved 10-04-2009. 2. Chu, S. (1998). Structured Design & Programming, Source;[ http://www.cs.runet.edu/( Radford University)], retrieved 10-04-2009. 3. Keith Shortridge, Horst Meyerdierks. (2004). Source; http://docs.jach.hawaii.edu/star/sun86.htx/node82.html, retrieved 10-04-2009 4. Lafore, R. (1999). Object Oriented Programming in C++ (éd. 3rd). Indiana: Sams Publishing. 5. Loudon, k. C. (1999). Management Information System (ed. 6th). New Jersey: Prentice-Hall.. Read More